code: def replicate_cudf_series(cudf_series):
      """
      Replicate series across all GPUs
  
      Parameters
      ----------
  
      cudf_series: cudf.Series or dask_cudf.Series
  
      Returns
      -------
      series : dask_cudf.Series
          A distributed series where each partition contains the
          combined series from all GPUs. If a cudf.Series was passed
          as input, the Series will be replicated across all the other
          GPUs in the cluster. If as dask_cudf.Series was passed as input,
          each partition will be filled with the series of all partitions
          in the dask_cudf.Series.
  
      """
  
      supported_types = [np.int32, np.int64, np.float32, np.float64]
      if cudf_series.dtype not in supported_types:
          raise TypeError(
              "The supported types are 'int32', 'int64', 'float32', 'float64'"
          )
  
      _client = default_client()
  
      if not isinstance(cudf_series, dask_cudf.Series):
          if isinstance(cudf_series, cudf.Series):
              series = dask_cudf.from_cudf(
                  cudf_series, npartitions=len(Comms.get_workers())
              )
          elif not isinstance(cudf_series, dask_cudf.Series):
              raise TypeError(
                  "The variable 'cudf_series' must be of type "
                  f"'cudf/dask_cudf.series', got type {type(cudf_series)}"
              )
      else:
          series = cudf_series
  
      series = persist_dask_df_equal_parts_per_worker(series, _client)
      series = get_persisted_df_worker_map(series, _client)
  
      series = _mg_call_plc_replicate(
          _client,
          Comms.get_session_id(),
          series,
          "series",
      )
  
      return series
  
file_path: cugraph/python/cugraph/cugraph/structure/replicate_edgelist.py
imports: import dask_cudf
  import cudf
  from dask.distributed import wait, default_client
  import numpy
  from pylibcugraph import ResourceHandle, replicate_edgelist
  from cugraph.dask.common.part_utils import get_persisted_df_worker_map, persist_dask_df_equal_parts_per_worker
  import dask
  import cupy
  import cugraph.dask.comms.comms
  from typing import Union, Tuple
label_desc: Use image node_id 8 for calling a global function with example usage: replicate_cudf_series(cudf_series) and returns: series